Maternal Immune-Mediated Conditions and ADHD Risk in Offspring

Maternal Immune-Mediated Conditions and ADHD Risk in Offspring | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Maternal Immune-Mediated Conditions and ADHD Risk in Offspring Kjersti Maehlum Walle, Kristin Gustavson, Siri Mjaaland, Ragna Bugge Askeland, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5594521/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2025 Read the published version in BMC Medicine → Version 1 posted 9 You are reading this latest preprint version Abstract BACKGROUND Maternal immune-mediated conditions during pregnancy have been linked with increased risk of attention-deficit/hyperactivity disorder (ADHD) in offspring. However, we do not know the extent to which these associations are influenced by shared genetic predispositions, as opposed to maternal inflammatory/immune responses during pregnancy. This study contributes by using paternal immune-mediated conditions as a negative control to explore these underlying factors, as we investigate associations between maternal immune-mediated conditions during pregnancy and offspring ADHD. METHODS Prospective data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) was linked with the Medical Birth Registry of Norway (MBRN) and the Norwegian Patient Registry (NPR) to assess associations between prenatal exposure to maternal immune-mediated conditions and offspring ADHD risk up to age 18. Nationwide recruitment from 1999 to 2008 resulted in 104,270 eligible mother-child pairs. Among these, 21,340 children were exposed to maternal allergic conditions (asthma, allergies, atopic conditions) and 7,478 to other immune conditions (autoimmune, inflammatory). Paternal self-reported immune conditions served as negative controls for genetic confounding. Data was mostly collected through MoBa, with additional maternal condition cases sourced from MBRN, and children’s ADHD diagnoses obtained from NPR. Cox proportional hazard models estimated Hazard ratios for ADHD diagnoses. RESULTS Both overall categories were associated with increased offspring ADHD risk (allergic conditions HR 1.23 95% CI, 1.14–1.34; other immune conditions HR 1.36 95% CI, 1.21–1.53). Specifically, we found associations for maternal asthma (HR 1.47 95% CI, 1.30–1.67); allergies (HR 1.20 95% CI, 1.10–1.31); rheumatologic/musculoskeletal conditions (HR 1.64 95% CI, 1.28–2.10), Crohn’s disease/ulcerative colitis (adjusted HR 1.95 95% CI, 1.23–3.09), and endocrine conditions (HR 1.42 95% CI, 1.15–1.77), specifically, type 1 diabetes (adjusted HR 2.50 95% CI, 1.66–3.75). Although some paternal immune-mediated conditions (psoriasis, ulcerative colitis, Crohn’s disease) showed similar trends of increased ADHD risk in offspring, only paternal asthma was significantly associated (adjusted HR 1.26 95% CI, 1.10–1.45). CONCLUSIONS Several maternal immune-mediated conditions were associated with increased ADHD risk in offspring. Observations of higher, more consistent estimates of ADHD risk in offspring for most maternal immune-mediated conditions versus paternal ones indicate that unmeasured genetic confounding does not fully explain these associations. These results suggest direct effects on fetal development through events at the maternal-fetal interface which may alter fetal immune responses and potentially lead to greater risk of ADHD in the offspring. Asthma may be a possible exception to this mechanism, as paternal asthma was also linked with risk of offspring ADHD. ADHD immune-mediated conditions pregnancy MoBa MBRN Figures Figure 1 Figure 2 Introduction Attention-deficit hyperactivity disorder (ADHD) is a common childhood psychiatric disorder 1 , with lifetime prevalence estimates by the age of 12 to be 5.4% among boys and 2.1% among girls in Norway being diagnosed 2 . Research into the origins of ADHD suggests a complex interplay of genetic and environmental factors 3 , with most environmental factors still regarded as correlates 3 . Among these, prenatal environmental factors such as prematurity, low birthweight, and maternal stress and substance use during pregnancy have been identified 4 – 8 . Recent studies suggest that immune and inflammatory pathways, as well as infectious exposures, may play roles in the development of ADHD 9 – 11 . This study examines two broad categories of maternal immune-mediated conditions as risk factors for offspring ADHD: 1) asthma, allergy, and atopic conditions (hereafter: allergic conditions) and 2) autoimmune and inflammatory conditions, including urticaria, psoriasis, Crohn’s disease (CD), ulcerative colitis (UC), coeliac disease, rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), fibromyalgia syndrome (FMS), type 1 diabetes (T1D), type 2 diabetes (T2D), gestational diabetes, and hyper/hypothyroidism (hereafter: other immune conditions). A central difference between these two broad categories is that allergic conditions involve exaggerated immune reactions to external triggers, while autoimmune and inflammatory conditions involve attack of the immune system on the body's own tissues, leading to chronic, systemic immune dysregulation and inflammation 12 . Allergic and other immune conditions often co-occur in individuals and families 13 – 16 , and mechanistic overlap exists, including activation of inflammatory cells and pathways 17 . However, variations in peripheral immune profiles, immune signaling pathways, cell types involved, and predominant immunoglobulin isotypes – such as immunoglobulin E (IgE) in allergic conditions versus immunoglobulin G (IgG) in inflammatory conditions 18 – 21 – suggest possible differing effects on fetal development. Therefore, different maternal immune-mediated conditions during pregnancy may also be differently associated with ADHD outcomes. Only a few studies have investigated ADHD risk after prenatal exposure to maternal immune-mediated conditions, and the associations with allergic and other immune conditions have rarely been compared within the same population. Current findings suggest both categories of conditions to be associated with ADHD risk 22 , possibly explained by immune processes happening during pregnancy 10 , 23 , 24 . The immune system's cells and proteins are integral to neurodevelopment and functioning 25 , 26 , and there is evidence that maternal autoantibodies, such as IgG antibodies, can transfer across the placenta 27 , 28 , or transfer indirectly as shown with IgE antibodies 29 . These maternal immune alterations may impact fetal development through mechanisms like epigenetic modulation of neurodevelopmental gene expression, regulation of microglia activity, and alteration of synaptic functions 23 , 24 , 30 . Discrepancies in immune pathogenesis between allergic and other immune conditions may modify risk levels, phenotypic manifestations, or severity of ADHD outcomes. Even within the immune categories, the presence of different autoantibodies or targets of cellular autoimmune attack may contribute to diverse outcomes. By assessing a range of allergic and other immune conditions within the same study population we aim to elucidate potential disparities in associations between different types or categories of immune-mediated disorders and ADHD risk. The different types of diabetes are also distinct in their underlying mechanisms, suggesting potential differences in how maternal exposure may impact fetal development and influence risk for neurodevelopmental outcomes such as ADHD. Whereas Type 1 Diabetes (T1D) is characterized by an autoimmune response involving autoantibodies against insulin-producing beta cells 31 , Type 2 Diabetes (T2D) and Gestational Diabetes are linked to insulin resistance and low-grade inflammation, influencing the maternal metabolic state 32 , 33 . This distinction warrants a separate analysis to more accurately assess impacts of autoimmune activation versus low-inflammation and metabolic influences on ADHD risk. This study explores associations between maternal immune-mediated conditions and offspring ADHD in a sample of 104 270 pairs of mothers and children from the Norwegian Mother, Father, and Child Cohort (MoBa). By using paternal immune-mediated conditions as a negative control, we aim to discern whether associations arise primarily from maternal inflammatory or immune responses during pregnancy or shared genetic predispositions. The study aims to: 1) estimate ADHD risk in offspring prenatally exposed to maternal immune-mediated conditions, and 2) assess the impact of unmeasured confounding using paternal immune-mediated conditions as a negative control. We hypothesize that maternal immune-mediated conditions during pregnancy increase the risk of ADHD in offspring, with differing impacts between different types of allergic and autoimmune/inflammatory conditions due to distinct immune and developmental pathways. Furthermore, we propose that the effect of maternal immune conditions on ADHD risk will be greater than paternal effects, highlighting the potential influence of environmental factors alongside genetic predispositions. Methods Study Population and Measures MoBa is a population-based pregnancy cohort study including approximately 114 500 children, 95 200 mothers and 75 200 fathers 34 , 35 . Pregnant women from across Norway (1999–2008) were enrolled, with 41% participation. The study uses quality-assured data, released for research in 2017 (v10), derived from maternal and paternal questionnaires completed at gestational weeks 17 and 30, as well as 6 months post-birth. MoBa data were linked to the Medical Birth Registry of Norway (MBRN), which holds comprehensive information on Norwegian births, including maternal diabetes, asthma, rheumatoid arthritis, age, parity, emigrations, and death records. The study was approved by The Regional Committee for Medical and Health Research Ethics (2014/2266). As low birth weight is associated with neonatal outcomes, and twins are more likely to be born with lower birth weight 36 , children from multiple births were excluded from our sample. Other exclusion criteria included congenital malformations due to complexity of their etiologies, which may involve multiple genetic, environmental, and unknown factors 37 ; death before the age of two; and unknown vital status (i.e., missing information on whether the child was alive or diseased at critical stages of the study timeline). Figure 1 displays numbers of participating and excluded mothers, fathers, and children. The final study sample included 104 270 children with mothers and 71 344 fathers. [Insert Fig. 1 here] Attention-Deficit/Hyperactivity Disorder Children's ADHD diagnoses were gathered from the Norwegian Patient Registry (NPR), which includes information from government-funded clinics in Norway following the ICD-10 revision. Diagnoses were obtained for children with ADHD (F90 code) registered in the NPR between 2008 and 2017. Maternal and Paternal Immune-Mediated Conditions Exposure variables were based primarily on parental self-report during pregnancy in MoBa questionnaires. Both parents reported their immune-mediated conditions by selecting from a list provided in a questionnaire (Table S1 ). Mothers also indicated if the condition occurred before and/or during pregnancy. To ensure clarity and avoid ambiguity in the variable categories, mothers reporting a specific immune-mediated condition before but not during pregnancy were excluded from the analyses related to that condition. However, exclusion from the analysis of a specific condition did not imply exclusion from the entire study. Additionally, there was information on three maternal immune-mediated conditions (diabetes, rheumatoid arthritis, and asthma) in MBRN, adding a few cases to our exposure variables for these conditions. As diagnoses were not person-identifiable in NPR prior to 2008, and most pregnancies occurred prior to this (1999–2008), we did not use NPR data to add cases in the exposure variables. We categorized immune-mediated conditions into two groups: 1) Asthma, allergy, and atopic conditions (allergic conditions), and 2) Autoimmune and inflammatory conditions (other immune conditions). Further subcategories included: 1a) asthma, 1b) allergies, 1c) atopic eczema, 1d) urticaria/hives, 2a) psoriasis, 2b) gastrointestinal conditions (Crohn’s disease (CD), ulcerative colitis (UC), coeliac disease), 2c) rheumatologic/musculoskeletal conditions (rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), fibromyalgia syndrome (FMS)), and 2d) endocrine conditions (type 1 diabetes (T1D), hyper/hypothyroidism). We categorized exposure conditions based on affected organs or tissues to leverage the available data effectively, allowing us to group conditions with similar immunological pathways and physiological impacts. This categorization provides a structured framework to explore distinct immune responses and their potential differential effects on ADHD risk. By aligning our categories with the biological basis of the conditions, we aim to enhance the precision of our analyses, grounding our findings in relevant physiological mechanisms. In negative control designs, we focused on maternal exposure conditions that had corresponding data collected from fathers, ensuring comparability between maternal and paternal information despite slight differences in the questionnaires. Due to the absence of queries regarding paternal thyroid conditions and restriction of paternal report to unspecified diabetes types, the negative control analysis for the endocrine category assessed overall diabetes for comparability between maternal and paternal exposure groups (Table S1 ). Using maternal data, we further investigated how exposure to different types of diabetes in pregnant mothers affected the risk of ADHD in offspring. Covariates To ensure that covariate selection was rooted in existing knowledge of relevant causal pathways, we first selected potential covariates based on previous research investigating maternal immune-mediated conditions as ADHD risk factors 22 , 38 – 42 , and available data. For each analysis we planned to conduct, covariates were evaluated for associations with both exposure and ADHD outcome to identify potential confounding. Directed acyclic graphs (DAGs) are effective tools for exploring complex causal relationships because they help clarify and visually represent pathways between variables 43 . This can prevent over-adjustment or unnecessary inclusion of covariates that do not contribute additional control, thereby reducing the risk of introducing collider bias or overfitting models 43 . We used Dagitty models 44 to define minimal sufficient adjustment sets of covariates for each specific analysis. Information on covariates selected is available in Table 1 (selection process details in Tables S2-4 and Figures S1 -10; handling of missing data described in Supplementary file). Statistical Analysis Analyses were performed using SPSS version 27 and Stata version 17. Crude and adjusted hazard ratios (HRs and aHRs) for ADHD with 95% confidence intervals (CIs) were estimated using Cox proportional hazard models. Separate analyses were conducted for each overall group and subgroups. The child’s age served as time variable, and follow-up started on the child’s third birthday, concluding with either an ADHD diagnosis, emigration, death, or by December 31st, 2017, whichever occurred first. Children were followed up until age 8–18 years. In our analysis, comparisons for one immune condition exposure (present/absent) included children who may have also been exposed to other immune conditions. To separate the effects of maternal immune-mediated responses during pregnancy from shared genetic factors, a negative control strategy was utilized. Previous studies have conducted negative control analyses by comparing outcomes of maternal exposures during pregnancy with paternal exposures or those of other relatives 7 , 45 . This approach tested associations between paternal immune-mediated conditions—which are not expected to directly impact the fetal environment beyond genetic/epigenetic effects—and offspring ADHD risk. Both maternal and paternal analyses are subject to similar confounding factors; however, except for paternal epigenetic influences and potential genetic effects on the placental environment 46 , maternal conditions predominantly affect the gestational milieu. Stronger associations with maternal immune-mediated conditions compared to paternal ones suggest an influence of maternal immune-mediated responses during pregnancy. Conversely, equal maternal and paternal associations imply that shared genetic and confounding factors are likely explanations. To prevent any bias that might occur if an observed association for one parent was driven by correlated conditions in the other parent, maternal and paternal associations were mutually adjusted for each other, as well as for the minimal sufficient adjustment sets of covariates. To address multiple testing – five tests within each family of tests (allergic conditions and other immune conditions) – we adjusted the alpha level to 0.01. Finally, sensitivity analyses examined the potential impact of folate use during pregnancy, recognizing its role in immune system balance 47 . Sensitivity analyses assessing effects of medical treatments were also performed. Results Descriptives Table 1 shows descriptive statistics for covariates. Amongst the children, 3 600 were diagnosed with ADHD (3.5%). [Insert Table 1 here] Overall Categories: Allergic and Other Immune Conditions Table 2 presents the risk estimates for the overall categories of maternal immune-mediated conditions. Both categories showed increased ADHD risk: allergic conditions (aHR = 1.23, CI: 1.14,1.34) and other immune conditions (aHR = 1.36, CI: 1.21,1.53). These findings suggest a broad impact of maternal immune health on offspring ADHD risk. [Insert Table 2 here] Asthma Asthma emerged as a significant factor in increasing ADHD risk. As indicated in Table 2, maternal asthma was associated with a substantial risk increase (aHR = 1.47, CI: 1.30,1.67). The negative control analysis in Fig. 2 pointed to a similar pattern with paternal asthma (aHR = 1.26, CI: 1.10,1.45), underscoring the importance of asthma in both maternal and paternal histories. [Insert Fig. 2 here] Allergies In examining allergies, and as can be seen in Table 2, we found that any maternal allergy increased ADHD risk (aHR = 1.20, CI: 1.10,1.31). Interestingly, Fig. 2 reveals contrasting effects of maternal and paternal pollen allergies, with maternal pollen allergies linked to elevated risk (aHR = 1.26, CI: 1.12,1.41), whereas paternal pollen allergies suggested a preventive effect (aHR = 0.81, CI: 0.72,0.92). This difference between maternal and paternal exposure was statistically significant (X2 (df = 1, N = 64167) = 26.49, p < .001). Gastrointestinal conditions Maternal gastrointestinal conditions overall (including the conditions Crohn’s disease (CD), ulcerative colitis (UC), and coeliac disease) did not reveal a significant association; however, the negative control analysis that specifically assessed Crohn’s disease and ulcerative colitis (CD/UC) revealed significant effects of maternal CD/UC (aHR = 1.95, CI: 1.23,3.09), but not of paternal CD/UC. Figure 2 shows that the hazard ratios for maternal versus paternal CD/UC were quite high; however, confidence intervals were wide, and the statistical difference only approached significance (X2 (df = 1, N = 70820) = 3.75, p = .053). Rheumatologic/Musculoskeletal Conditions The overall category of maternal rheumatologic/musculoskeletal conditions (including the conditions rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus, and fibromyalgia syndrome) were in the initial analysis associated with increased ADHD risk (aHR = 1.64, CI: 1.28,2.10). However, the exposure in the negative control analysis was limited to assess the conditions RA and AS and showed a similar trend for maternal exposure but not for paternal exposure. Endocrine Conditions and Diabetes Maternal endocrine conditions (including type 1 diabetes (T1D) and thyroid conditions) showed an increased risk of offspring ADHD (aHR = 1.42, CI:1.15,1.77). The negative control analysis, investigating any type of diabetes, displayed an effect of maternal diabetes (aHR = 1.39, 95% CI: 1.02,1.90) but not one of paternal diabetes. Analyzing type 1 diabetes (T1D), type 2 diabetes (T2D) and gestational diabetes (GD) separately (mothers only), offspring ADHD risk increased only with maternal T1D (aHR 2.50, 95% CI:1.66–3.75) (Table 3). No significant associations were noted for maternal type 2 diabetes (T2D) and gestational diabetes (GD). [Insert Table 3 here] Sensitivity Analyses Sensitivity analyses (Table S9-10 in supplementary file) found no interactions between folic acid and specific conditions, or any effects of medical treatments on offspring ADHD risk. Discussion Our findings suggest that maternal immune-mediated conditions, both allergic and other immune conditions, are associated with a higher risk of ADHD in offspring. Specifically, maternal asthma is associated with a 47% higher risk, allergies with a 20% higher risk, rheumatologic/musculoskeletal conditions with a 64% higher risk, and endocrine conditions with a 42% higher risk. When examining a smaller sample with information on both paternal and maternal conditions available, asthma was the only paternal condition linked to an increased ADHD risk in offspring, showing a 26% higher risk. In comparison, for maternal conditions increased risk of ADHD in offspring was found with; asthma (33% higher risk), pollen allergies (26% higher risk), Crohn's disease/ulcerative colitis (CD/UC) (95% higher risk), and any type of diabetes (39% higher risk). Notably, the difference in risk between maternal and paternal conditions was only significant for pollen allergies, where maternal and paternal associations showed opposing directions. Comparison of maternal diabetes subtypes revealed that type 1 diabetes was associated with a 150% higher risk of ADHD in offspring, while type 2 diabetes and gestational diabetes were not significantly associated with ADHD risk. This underscores the role of type 1 diabetes in the observed association between any maternal diabetes and ADHD risk. Information on the diabetes type was not available for fathers, limiting our analysis of paternal diabetes. This study consistently found higher ADHD risk associated with maternal immune-mediated conditions compared to paternal ones, particularly allergies, which showed significant directional differences. While maternal conditions uniformly showed trends toward increased ADHD risk, paternal conditions exhibited more variability, with only asthma showing a significant association. Previous research has indicated higher ADHD risk after exposure to maternal, compared to paternal, autoimmune and atopic disorders, with similar findings regarding risk of autism spectrum disorder (autism) 48 , suggesting potential maternal-specific immune mechanisms during pregnancy. Maternal Immune Activation and Fetal Development Maternal exposure to immune-mediated conditions during pregnancy could heighten offspring ADHD risk through mechanisms involving maternal immune activation, likely impacting fetal development via the placenta 49 . Research on "fetal programming" underscores the placenta's significance as the first functional organ of the fetus, facilitating maternal-fetal cellular interactions 24 , 50 – 53 , which may influence fetal immune system development 50 . Disruptions in these interactions may potentially contribute to neuropsychiatric conditions like ADHD and autism 54 , 55 . Studies associating neurodevelopmental conditions and traits with prenatal exposure to maternal antibodies 56 suggest that maternal immune-mediated conditions may impact neurodevelopment through antibody-mediated pathways, including potential transference across the placenta and placental cytokine expression. Different maternal immune conditions can uniquely impact fetal development through a range of mechanisms, some of which overlap while others are distinct, as detailed in the following sections. These mechanisms encompass aspects, such as immune activation, response shifts, antibody transfer, metabolic influences, dopaminergic system interactions, and genetic and epigenetic factors. Maternal Immune Response Shifts during Pregnancy During normal pregnancies, the maternal immune response shifts from Th1 (cell-mediated) to Th2 (humoral) dominance 49 , reducing inflammatory cytokine production, while increasing regulatory T-cell (Treg) production 49 , 57 . This shift can have varying implications for maternal immune-mediated conditions. Atopic conditions, such as asthma and allergies, are typically Th2-dominant, and the enhanced Th2 response during pregnancy could exacerbate these conditions due to increased humoral activity 58 . Conversely, autoimmune conditions (such as RA, CD, UC) that are predominantly Th1-mediated may experience symptom improvement during pregnancy, as the Th2 shift downregulates typical inflammatory pathways 59 . However, this shift in maternal immune response also results in elevated anti-inflammatory cytokine levels in maternal blood 49 , which again may influence brain development pathways. Evidence from animal models suggests that maternal immune activation may reduce the accumulation of Tregs at the maternal-fetal interface, and that reversing this may reduce adverse neurodevelopmental outcomes 60 . The mechanism by which maternal immune molecules influence fetal immune system and neurodevelopment, therefore, remains uncertain 24 . The placenta may play a pivotal role in modulating these effects. It contains its own macrophages, Hofbauer cells, producing various cytokines and chemokines 61 . In response to maternal inflammation, the placenta may release cytokines and chemokines into fetal circulation, potentially affecting ongoing fetal growth and neurodevelopment 49 , 62 , 63 . Cytokine release and subsequent inflammation are also key factors in altering dopaminergic systems, a feature strongly associated with ADHD. Moreover placental inflammation can activate microglia 49 , immune cells essential for neurodevelopmental processes, including axon guidance and synapses pruning 64 , 65 . Activated excessively, microglia can release pro-inflammatory cytokines and proteins, potentially harming neurons and disrupting neurodevelopment 66 , 67 . Neurodevelopmental effects may also be mediated by activation of placental Toll-like receptors, which respond to various environmental threats 68 . Since Th2 dominance during pregnancy may result in exaggerated anti-inflammatory responses that intensify atopic conditions such as asthma and allergies 58 , this heightened immune activity could amplify its influence on fetal development, potentially altering neurodevelopmental pathways and increasing ADHD risk. Autoimmune conditions characterized by Th1 dominance may experience symptom improvement during pregnancy due to reduced inflammation 59 , potentially diminishing the fetal risk associated with maternal exposure to these conditions. 58 Placental Antibody Transfer Initially, only IgG antibodies were believed to cross the placenta, typically from the 13th week of gestation 69 . IgG autoantibodies play a significant role in autoimmune and inflammatory conditions, such as rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), fibromyalgia syndrome (FMS) 21 , 70 , 71 , and this study found associations between maternal rheumatologic musculoskeletal conditions, especially SLE and FMS, and ADHD risk. Maternal SLE has previously been linked to increased risk of neurodevelopmental disorders or other developmental challenges, particularly in boys 72 , possibly due to placental transfer of maternal IgG autoantibodies 73 , 74 . Similarly, transferring IgG autoantibodies from FMS patients to mice has been shown to induce sensory hypersensitivity, suggesting a potential mechanism for maternal FMS impacting offspring neurodevelopment 71 . While placental transfer of IgG antibodies is long recognized, recent evidence suggests that IgE autoantibodies can also be transferred across the placenta, though indirectly through immune complex linkage 27 – 29 . Atopic conditions like asthma and allergies often involve elevated IgE levels 21 . Maternal asthma and allergies were associated with offspring ADHD risk, and effect estimates were higher than for paternal exposure. Elevated IgE and resulting inflammation may contribute to irregularities in fetal brain development. The trend of higher ADHD risk after prenatal exposure to maternal eczema only approached significance, which could be due to the lack of differentiation between intrinsic and extrinsic types of eczema, which are associated with different levels of IgE 75 . On the other hand, another study that measured prenatal IgE did not find an association with offspring ADHD outcomes 76 , which underscores the need for further research. Dopaminergic System and Immune Interaction Impairments in the dopaminergic system are recognized as a significant mechanism in ADHD 77 , 78 , with studies linking genes like dopamine receptor D4 and the dopamine transporter to the disorder 79 . Dopamine receptors on immune cells suggest dopamine involvement in immune-inflammatory responses 80 . Dysregulation of peripheral dopamine levels is linked to rheumatoid arthritis and inflammatory bowel disease 80 , 81 . Alterations in dopamine pathways due to maternal immune conditions could contribute to the increased ADHD risk observed in offspring. Maternal immune activation in rats affects offspring dopaminergic signaling 62 , and, given dopamine’s role in ADHD 77 and immune disorders 62 , 80 , dopamine dysregulation presents a common mechanism and plausible link. Our study supports this, showing increased ADHD risk with maternal rheumatologic/musculoskeletal conditions and maternal CD/UC. Diabetes and ADHD Risk - autoimmune inflammation vs metabolic influences We observed a strong association between maternal Type 1 Diabetes (T1D) and the risk of ADHD in offspring, consistent with previous research 22 , 38 , 40 – 42 . Despite few maternal T1D cases in the diabetes group (N = 301 of 1 425), analyzed separately, maternal T1D HR was notably high (HR = 2.5). In contrast, other diabetes types such as maternal Type 2 Diabetes (T2D) and Gestational Diabetes Mellitus (GDM) showed no individual associations with offspring ADHD risk. Unfortunately, fathers did not specify diabetes type, limiting direct comparison of maternal and paternal T1D exposure. Instead, the broader exposure category “any diabetes” was compared between mothers and fathers. Any maternal diabetes exposure had higher HRs than any paternal diabetes, though not significantly different. This could be due to the inclusion of all diabetes types causing group heterogeneity. GDM, emerging during pregnancy 82 , shares features like insulin resistance with T2D and lacks T1D’s autoimmune aspect 33 . While T1D involves autoantibodies against insulin-producing cells 31 , T2D’s immune role centers on low-grade inflammation and insulin resistance 32 , 33 . The significant increase in offspring ADHD risk with maternal T1D, and not with other diabetes types, may be explained by the autoimmune inflammation impacting fetal neural development, in contrast to the metabolic influences of other diabetes types. Genetic and Epigenetic Influences Maternal and paternal asthma were both linked to offspring ADHD, aligning with recent cohort studies in Denmark and Taiwan 48 , 83 . A recent meta-analysis also reported a phenotypic association between ADHD and asthma, suggesting shared familial factors (genetic liability and/or shared environmental factors) contributing to their risk 84 . ADHD and many immune-mediated conditions have heritable components 85 – 87 and their high comorbidity 38 , 88 suggest shared genetic variations. Genetic and epigenetic factors, influencing gene expression timing and location, and possibly influenced by prenatal environment 89 , are implicated in autoimmune and atopic disorder development 90 . These genetic and epigenetic changes could affect brain development processes, contributing to ADHD expression. Research suggests that epigenetic modifiers affecting DNA methylation (DNAm) and histone remodeling are crucial for normal neurodevelopment 91 . DNAm is extensively studied as an epigenetic marker of ADHD 89 , due to its role in brain maturation and function 92 , susceptibility to genetic and environmental influences 93 , 94 , and links to various health issues, including immune-mediated conditions 95 and psychiatric disorders 91 . Strengths and limitations This study has several strengths. Data were drawn from an extensive birth cohort, facilitating detection of nuanced differences in ADHD risk across various groups and allowing for comparison between maternal gestational exposure and paternal exposure, offering insights into the complex interplay of environmental and genetic factors. Prospective data collection spanned multiple pregnancy exposures, with 8–18 years of follow-up. Additionally, the alpha level was adjusted to mitigate the risk of false positives. The study has limitations that could impact generalizability. Firstly, the 41% participation rate in MoBa could introduce selection bias, as participants are typically healthier and better educated than the overall population 96 , 97 . However, previous research found associations between various exposures and outcomes in MoBa participants and the total population to be comparable 96 , 97 . Children with ADHD in MoBa show similar functioning and psychosocial challenges as those in the broader Norwegian population 98 . Simulations suggest that associations between risk factors and health outcomes remain robust even with underrepresented groups in the sample 99 . Secondly, the oldest children in the sample may have received ADHD diagnoses before individual diagnoses were recorded in NPR, potentially resulting in false negatives if they only sought specialist healthcare in their early years(< 2008). Thirdly, self-reported medical conditions may be biased. Men with symptoms similar to women may receive more thorough treatment 100 , potentially affecting diagnosis rates. Moreover, unclear distinctions between immune disease types and diagnosis delays 101 can impact report accuracy. Reliable research depends on accurate data collection; misclassification of cases can dilute the effects. Fourthly, there is a significant amount of missing data for maternal ADHD symptoms, with approximately 49% missing. Although we used multiple imputation to address this issue, it is possible that the data missingness is not random, as ADHD symptoms could affect the likelihood of completing questionnaires. The results should therefore be interpreted with this consideration in mind. Fifthly, we acknowledge that some covariates might not have shown significant associations due to measurement imperfections or sample-specific characteristics, potentially leading to their exclusion despite theoretical relevance. Also, ~ 70% of fathers lacked information regarding ADHD symptoms. Consequently, we did not include paternal ADHD symptoms as a covariate, though this could be a potential confounder, particularly between paternal immune-mediated conditions and offspring ADHD. However, significant associations between maternal immune-mediated conditions and offspring ADHD persisted after adjusting for maternal ADHD symptoms. Conversely, associations with paternal conditions were weaker, even without adjusting for paternal ADHD symptoms. Sixthly, comparisons made for one immune condition exposure could include children exposed to additional immune conditions, which complicates the isolation of the specific impact of each condition. Seventhly, our data on asthma is not specific with regards to atopy. Eightly, in analyses comparing maternal gestational immune-mediated conditions with paternal immune-mediated conditions, paternal influence during gestation cannot be discounted, given animal studies indicating the paternal genome may impact placental development through genomic imprinting 102 . Lastly, maternal medical treatment during gestation, could affect associations. However, sensitivity analyses revealed no interactions between medical treatments and conditions. Conclusion This large population-based cohort revealed increased offspring ADHD risk when mothers had certain immune-mediated conditions during pregnancy. Paternal asthma was also associated with offspring ADHD, implying some shared mechanisms involving genetic/epigenetic influences established at the time of conception. Maternal conditions may additionally have direct effects on fetal development through the maternal-fetal interface, potentially altering immune responses and increasing ADHD risk. The complex interplay of genetic/epigenetic, immune, environmental, and placental factors likely contributes to these associations. Further research is needed to explore the specific genetic and epigenetic pathways, as well as to identify precise immune and environmental factors that may mediate these risks. Longitudinal studies incorporating advanced biomarker analyses and detailed environmental exposure assessments could provide more comprehensive insights into the causal pathways and potential intervention points. Additionally, investigating whether these findings are consistent across diverse populations and settings would enhance the generalizability of our conclusions. Abbreviations ADHD Attention–deficit/hyperactivity disorder MoBa The Norwegian Mother, Father, and Child Cohort Study MBRN The Medical Birth Registry of Norway NPR The Norwegian Patient Registry IgE Immunoglobulin E IgG Immunoglobulin G CD Crohn’s disease UC Ulcerative colitis RA Rheumatoid arthritis AS Ankylosing spondylitis SLE Systemic lupus erythematosus FMS Fibromyalgia syndrome T1D Type 1 diabetes Declarations Ethics approval and consent to participate The study was approved by The Regional Committee for Medical and Health Research Ethics (2014/2266). Consent for publication Not applicable. Availability of data and materials Data from the Norwegian Mother, Father and Child Cohort Study and the Medical Birth Registry of Norway used in this study are managed by the national health register holders in Norway (Norwegian Institute of public health) and can be made available to researchers, provided approval from the Regional Committees for Medical and Health Research Ethics (REC), compliance with the EU General Data Protection Regulation (GDPR) and approval from the data owners. The consent given by the participants does not open for storage of data on an individual level in repositories or journals. Researchers who want access to data sets for replication should apply through helsedata.no. Access to data sets requires approval from The Regional Committee for Medical and Health Research Ethics in Norway and an agreement with MoBa. Competing interests The authors declare that they have no competing interests. Funding Funding is provided by the National Institute of Child Health and Human Development (NICHD), Grant/Award Number: R01HD090051, and by The Research Council of Norway, Grant/Award Number: 248983. Authors' contributions All authors (KMW, RBA, KG, SM, PM, ES, WIL, CS, MB, TRK, MH, HA) contributed to the planning of the project, including research questions, design, use of methods, etc. KMW cleaned and analyzed the data. KG provided statistical advice. KMW prepared all tables and figures. All authors interpreted results. KMW drafted the manuscript. All authors contributed to revise the manuscript, and all approved the final manuscript. Acknowledgements The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this on-going cohort study. 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Proceedings of the National Academy of Sciences . 2013;110(26):10705-10710. doi:doi:10.1073/pnas.1308998110 Tables TABLE 1 Descriptive Statistics for Covariates Total Sample, n = 104270 Birth year, n , mean, [SD] 104 270 2005 [2,217] Mothers’ age, n, mean, [SD] 104 270 30,1 [4,666] Mothers’ ADHD symptoms' score, n , mean, [SD] 52 947 2,1 [0,576] Missing data on mothers’ ADHD symptoms’ scores, n, (%) 51 322 (49,22) Highest level of education among parents, n, (%) Less than high school graduate 3 495 (3,35) High school graduate 23 250 (22,30) Undergraduate education completed 34 055 (32,66) Postgraduate education (masters or doctorate) completed 28 754 (27,58) Missing data on level of education 14 715 (14,11) Parents’ relationship status, n, (%) Married or in a relationship 90 754 (87,04) Single 3 181 (3,05) Missing data on parents’ relationship status 10 334 (9,91) Parity, n, (%) First born 45 545 (43,68) Second born 37 678 (36,14) Third (or more) born 21 046 (20,18) Mother's smoking habits, n, (%) Mothers smoking before pregnancy 26 326 (25,25) Mothers not smoking before pregnancy 66 269 (63,56) Missing data on smoking habits 11 674 (11,20) Alcohol use before pregnancy, n, (%) Never 6 555 (6,29) Less than 3 units per month 57 620 (55,26) 1-3 units per week 22 489 (21,57) 4-7 units per week 948 (0,91) Missing data on alcohol use 16 657 (15,98) The mother’s previous mental disorders, n, (%) Previously diagnosed with anorexia, bulimia, or other eating aadisorders, depression or anxiety 19 264 (18,48) Never diagnosed with anorexia, bulimia, or other.eating a disorders, depression or anxiety 85 005 (81,52) TABLE 2 Associations Between Maternal Immune-Mediated Conditions During Pregnancy and ADHD in Offspring Examined with Cox Proportional Hazard Analyses Crude Adjusted a No, of Person-Months at observed risk b Incidence Rate c Hazard Ratio SE 95% CI P Hazard Ratio SE 95% CI P Asthma/Allergic/Atopic Conditions No 10016598 22,6 Ref Ref Yes 3106811 27,0 1,20 0,05 1,11-1,30 <,001 1,23 0,05 1,14-1,34 <,001 Autoimmune/ Inflammatory Conditions No 13948303 23,0 Ref Ref Yes 1078983 29,9 1,31 0,08 1,17-1,47 <,001 1,36 0,08 1,21-1,53 <,001 Asthma No 13939521 22,6 Ref Ref Yes 743603 36,3 1,61 0,1 1,42-1,83 <,001 1,47 0,09 1,30-1,67 <,001 Any Allergy (pollen, animal, other) No 11181584 23,3 Ref Ref Yes 2385555 26,3 1,14 0,05 1,04-1,24 0,004 1,20 0,05 1,10-1,31 <,001 Atopic Eczema No 14248317 23,6 Ref Ref Yes 548285 24,8 1,06 0,09 0,89-1,26 0,528 1,13 0,10 0,95-1,34 0,176 Urticaria/Hives No 14625830 23,6 Ref Ref Yes 110415 26,3 1,11 0,21 0,77-1,60 0,584 1,11 0,21 0,77-1,60 0,574 Psoriasis No 14815126 23,6 Ref Ref Yes 239105 28,0 1,19 0,15 0,93-1,51 0,162 1,14 0,14 0,89-1,45 0,296 Gastrointestinal Conditions No 15052760 23,7 Ref Ref Yes 108500 27,6 1,20 0,23 0,83-1,73 0,340 1,28 0,24 0,89-1,85 0,189 Rheumatologic/Musculoskeletal Conditions No 14966233 23,4 Ref Ref Yes 154198 42,2 1,80 0,23 1,41-2,31 <,001 1,64 0,21 1,28-2,10 <,001 Endocrine Conditions No 14609045 23,4 Ref Ref Yes 298589 30,5 1,32 0,14 1,07-1,63 0,011 1,42 0,15 1,15-1,77 0,001 Note: Separate analyses were performed for each of the exposure variables. CI, Confidence interval; Ref, reference group to which mothers with immune-mediated disorders are compared. The α level was set to .01 to indicate significant associations. a Each analyses used specific adjustment sets of covariates: Asthma/Allergic/Atopic Conditions: child's birth year, mother's parity, alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Autoimmune/Inflammatory Conditions: child's birth year, parental relationship status, mother's age, parity, smoking and alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Asthma: parental relationship status, mother's age, parity, smoking and alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Any Allergy: child's birth year, parental educational attainment, mother's age, parity, smoking and alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Atopic Eczema: child's birth year, parental educational attainment, mother's parity, alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Urticaria/Hives: parental educational attainment, mother's parity and alcohol use before pregnancy; Psoriasis: parental educational attainment and relationship status, mother's smoking and previous mental disorders; Gastrointestinal Conditions: child's birth year, mother's age and previous mental disorders; Rheumatologic/Musculoskeletal Conditions: parental educational attainment and relationship status, mother's parity, smoking and alcohol use before pregnancy, and self‐reported ADHD symptoms; Endocrine Conditions (T1D and hyper/hypothyroidism): child's birth year, parental educational attainment, mother's age, parity, smoking and alcohol use before pregnancy, and self‐reported ADHD symptoms. b Observation period between January 2008 and December 2017 for participants born in or before January 2008. c Per 100 000 person-months under observed risk. TABLE 3 Associations Between Different Types of Maternal Diabetes in Pregnancy and ADHD in Offspring Examined with Cox Proportional Hazard Analyses Crude Adjusted a No, of Person-Months at observed risk b Incidence Rate c Hazard Ratio SE 95% CI P Hazard Ratio SE 95% CI P Diabetes 1 No 14972880 23,5 Ref Ref Yes 43263 57,8 2,48 0,51 1,66-3,73 <,001 2,5 0,52 1,66-3,75 <,001 Diabetes 2 No 14972880 23,5 Ref Ref Yes 21993 22,7 0,98 0,22 0,64-1,52 0,944 0,98 0,22 0,64-1,52 0,940 Gestational diabetes No 14972880 23,5 Ref Ref Yes 140489 27,8 1,05 0,04 0,97-1,13 0,259 1,04 0,04 0, 96-1,12 0,341 Note: Separate analyses were performed for each type of diabetes. CI, Confidence interval; Ref, reference group to which mothers with diabetes are compared. The α level was set to .01 to indicate significant associations. a Analyses are adjusted for the following covariates: child's birth year, parental educational attainment, mother's age, parity, smoking and alcohol use before pregnancy, and self‐reported ADHD symptoms. b Observation period between January 2008 and December 2017 for participants born in or before January 2008. c Per 100 000 person-months under observed risk. Additional Declarations No competing interests reported. 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Ian Lipkin","email":"","orcid":"","institution":"Columbia University Mailman School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"W.","middleName":"Ian","lastName":"Lipkin","suffix":""},{"id":440872842,"identity":"b2461446-6d37-4345-b397-60d99c594918","order_by":7,"name":"Camilla Stoltenberg","email":"","orcid":"","institution":"University of Bergen","correspondingAuthor":false,"prefix":"","firstName":"Camilla","middleName":"","lastName":"Stoltenberg","suffix":""},{"id":440872843,"identity":"c1f727ba-84e4-419c-9d1a-455b8c5ec9e1","order_by":8,"name":"Michaeline Bresnahan","email":"","orcid":"","institution":"Columbia University Mailman School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Michaeline","middleName":"","lastName":"Bresnahan","suffix":""},{"id":440872844,"identity":"58822e82-0c29-40fe-a816-97a4daa640a2","order_by":9,"name":"Ted Reichborn-Kjennerud","email":"","orcid":"","institution":"Norwegian Institute of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Ted","middleName":"","lastName":"Reichborn-Kjennerud","suffix":""},{"id":440872845,"identity":"03db10bb-41bb-46a8-906c-c63a4b35955e","order_by":10,"name":"Mady Hornig MA","email":"","orcid":"","institution":"Columbia University Mailman School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Mady","middleName":"Hornig","lastName":"MA","suffix":""},{"id":440872846,"identity":"b5db7b4e-1862-4f4c-a231-d29b29e528c8","order_by":11,"name":"Helga Ask","email":"","orcid":"","institution":"Norwegian Institute of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Helga","middleName":"","lastName":"Ask","suffix":""}],"badges":[],"createdAt":"2024-12-06 14:38:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5594521/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5594521/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12916-025-04227-3","type":"published","date":"2025-07-01T15:58:34+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80579886,"identity":"5da43467-47f1-46a6-9990-2fbd5a81921a","added_by":"auto","created_at":"2025-04-14 23:10:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":16712,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow Chart of Inclusion of Participants\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"OnlineFigure1TIFF17cm.png.png","url":"https://assets-eu.researchsquare.com/files/rs-5594521/v1/c5e8e0b13276c0441791ebda.png"},{"id":80578436,"identity":"7bc5441d-8cb1-4f3f-9bd1-e05b331af3f0","added_by":"auto","created_at":"2025-04-14 23:02:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":41118,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest Plot Comparing Hazard Ratios for ADHD after Maternal and Paternal Immune-Mediated Conditions\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"OnlineFigure2newtiff.png","url":"https://assets-eu.researchsquare.com/files/rs-5594521/v1/6c37533a74a2c1cad7fdce12.png"},{"id":86179224,"identity":"04817cb1-0b29-4ee6-a5d3-94eb9b56ef3e","added_by":"auto","created_at":"2025-07-07 16:17:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1145978,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5594521/v1/ab9184fc-18c2-46de-97c0-6864b67925fc.pdf"},{"id":80578446,"identity":"65914c08-407b-42c2-9e53-4dff814aa7eb","added_by":"auto","created_at":"2025-04-14 23:02:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3453453,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfileeditedcleanversion.docx","url":"https://assets-eu.researchsquare.com/files/rs-5594521/v1/fa1a79ac8df7279c6b8ffa37.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maternal Immune-Mediated Conditions and ADHD Risk in Offspring","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAttention-deficit hyperactivity disorder (ADHD) is a common childhood psychiatric disorder\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, with lifetime prevalence estimates by the age of 12 to be 5.4% among boys and 2.1% among girls in Norway being diagnosed\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Research into the origins of ADHD suggests a complex interplay of genetic and environmental factors\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, with most environmental factors still regarded as correlates\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Among these, prenatal environmental factors such as prematurity, low birthweight, and maternal stress and substance use during pregnancy have been identified\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e–\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Recent studies suggest that immune and inflammatory pathways, as well as infectious exposures, may play roles in the development of ADHD\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR10\" class=\"CitationRef\"\u003e9\u003c/span\u003e–\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study examines two broad categories of maternal immune-mediated conditions as risk factors for offspring ADHD: 1) asthma, allergy, and atopic conditions (hereafter: allergic conditions) and 2) autoimmune and inflammatory conditions, including urticaria, psoriasis, Crohn’s disease (CD), ulcerative colitis (UC), coeliac disease, rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), fibromyalgia syndrome (FMS), type 1 diabetes (T1D), type 2 diabetes (T2D), gestational diabetes, and hyper/hypothyroidism (hereafter: other immune conditions). A central difference between these two broad categories is that allergic conditions involve exaggerated immune reactions to external triggers, while autoimmune and inflammatory conditions involve attack of the immune system on the body's own tissues, leading to chronic, systemic immune dysregulation and inflammation\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAllergic and other immune conditions often co-occur in individuals and families\u003csup\u003e\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e13\u003c/span\u003e–\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and mechanistic overlap exists, including activation of inflammatory cells and pathways\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, variations in peripheral immune profiles, immune signaling pathways, cell types involved, and predominant immunoglobulin isotypes – such as immunoglobulin E (IgE) in allergic conditions versus immunoglobulin G (IgG) in inflammatory conditions\u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e18\u003c/span\u003e–\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e – suggest possible differing effects on fetal development. Therefore, different maternal immune-mediated conditions during pregnancy may also be differently associated with ADHD outcomes.\u003c/p\u003e\u003cp\u003eOnly a few studies have investigated ADHD risk after prenatal exposure to maternal immune-mediated conditions, and the associations with allergic and other immune conditions have rarely been compared within the same population. Current findings suggest both categories of conditions to be associated with ADHD risk\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, possibly explained by immune processes happening during pregnancy\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The immune system's cells and proteins are integral to neurodevelopment and functioning\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, and there is evidence that maternal autoantibodies, such as IgG antibodies, can transfer across the placenta \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, or transfer indirectly as shown with IgE antibodies\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. These maternal immune alterations may impact fetal development through mechanisms like epigenetic modulation of neurodevelopmental gene expression, regulation of microglia activity, and alteration of synaptic functions\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDiscrepancies in immune pathogenesis between allergic and other immune conditions may modify risk levels, phenotypic manifestations, or severity of ADHD outcomes. Even within the immune categories, the presence of different autoantibodies or targets of cellular autoimmune attack may contribute to diverse outcomes. By assessing a range of allergic and other immune conditions within the same study population we aim to elucidate potential disparities in associations between different types or categories of immune-mediated disorders and ADHD risk.\u003c/p\u003e\u003cp\u003eThe different types of diabetes are also distinct in their underlying mechanisms, suggesting potential differences in how maternal exposure may impact fetal development and influence risk for neurodevelopmental outcomes such as ADHD. Whereas Type 1 Diabetes (T1D) is characterized by an autoimmune response involving autoantibodies against insulin-producing beta cells\u003csup\u003e31\u003c/sup\u003e, Type 2 Diabetes (T2D) and Gestational Diabetes are linked to insulin resistance and low-grade inflammation, influencing the maternal metabolic state\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This distinction warrants a separate analysis to more accurately assess impacts of autoimmune activation versus low-inflammation and metabolic influences on ADHD risk.\u003c/p\u003e\u003cp\u003eThis study explores associations between maternal immune-mediated conditions and offspring ADHD in a sample of 104 270 pairs of mothers and children from the Norwegian Mother, Father, and Child Cohort (MoBa). By using paternal immune-mediated conditions as a negative control, we aim to discern whether associations arise primarily from maternal inflammatory or immune responses during pregnancy or shared genetic predispositions. The study aims to: 1) estimate ADHD risk in offspring prenatally exposed to maternal immune-mediated conditions, and 2) assess the impact of unmeasured confounding using paternal immune-mediated conditions as a negative control.\u003c/p\u003e\u003cp\u003eWe hypothesize that maternal immune-mediated conditions during pregnancy increase the risk of ADHD in offspring, with differing impacts between different types of allergic and autoimmune/inflammatory conditions due to distinct immune and developmental pathways. Furthermore, we propose that the effect of maternal immune conditions on ADHD risk will be greater than paternal effects, highlighting the potential influence of environmental factors alongside genetic predispositions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy Population and Measures\u003c/p\u003e\u003cp\u003eMoBa is a population-based pregnancy cohort study including approximately 114 500 children, 95 200 mothers and 75 200 fathers\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Pregnant women from across Norway (1999–2008) were enrolled, with 41% participation. The study uses quality-assured data, released for research in 2017 (v10), derived from maternal and paternal questionnaires completed at gestational weeks 17 and 30, as well as 6 months post-birth. MoBa data were linked to the Medical Birth Registry of Norway (MBRN), which holds comprehensive information on Norwegian births, including maternal diabetes, asthma, rheumatoid arthritis, age, parity, emigrations, and death records. The study was approved by The Regional Committee for Medical and Health Research Ethics (2014/2266).\u003c/p\u003e\u003cp\u003eAs low birth weight is associated with neonatal outcomes, and twins are more likely to be born with lower birth weight\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, children from multiple births were excluded from our sample. Other exclusion criteria included congenital malformations due to complexity of their etiologies, which may involve multiple genetic, environmental, and unknown factors\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e; death before the age of two; and unknown vital status (i.e., missing information on whether the child was alive or diseased at critical stages of the study timeline). Figure\u0026nbsp;1 displays numbers of participating and excluded mothers, fathers, and children. The final study sample included 104 270 children with mothers and 71 344 fathers.\u003c/p\u003e\u003cp\u003e[Insert Fig.\u0026nbsp;1 here]\u003c/p\u003e\u003cp\u003eAttention-Deficit/Hyperactivity Disorder\u003c/p\u003e\u003cp\u003eChildren's ADHD diagnoses were gathered from the Norwegian Patient Registry (NPR), which includes information from government-funded clinics in Norway following the ICD-10 revision. Diagnoses were obtained for children with ADHD (F90 code) registered in the NPR between 2008 and 2017.\u003c/p\u003e\u003cp\u003eMaternal and Paternal Immune-Mediated Conditions\u003c/p\u003e\u003cp\u003eExposure variables were based primarily on parental self-report during pregnancy in MoBa questionnaires. Both parents reported their immune-mediated conditions by selecting from a list provided in a questionnaire (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Mothers also indicated if the condition occurred before and/or during pregnancy. To ensure clarity and avoid ambiguity in the variable categories, mothers reporting a specific immune-mediated condition before but not during pregnancy were excluded from the analyses related to that condition. However, exclusion from the analysis of a specific condition did not imply exclusion from the entire study. Additionally, there was information on three maternal immune-mediated conditions (diabetes, rheumatoid arthritis, and asthma) in MBRN, adding a few cases to our exposure variables for these conditions. As diagnoses were not person-identifiable in NPR prior to 2008, and most pregnancies occurred prior to this (1999–2008), we did not use NPR data to add cases in the exposure variables.\u003c/p\u003e\u003cp\u003eWe categorized immune-mediated conditions into two groups: 1) Asthma, allergy, and atopic conditions (allergic conditions), and 2) Autoimmune and inflammatory conditions (other immune conditions). Further subcategories included: 1a) asthma, 1b) allergies, 1c) atopic eczema, 1d) urticaria/hives, 2a) psoriasis, 2b) gastrointestinal conditions (Crohn’s disease (CD), ulcerative colitis (UC), coeliac disease), 2c) rheumatologic/musculoskeletal conditions (rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), fibromyalgia syndrome (FMS)), and 2d) endocrine conditions (type 1 diabetes (T1D), hyper/hypothyroidism). We categorized exposure conditions based on affected organs or tissues to leverage the available data effectively, allowing us to group conditions with similar immunological pathways and physiological impacts. This categorization provides a structured framework to explore distinct immune responses and their potential differential effects on ADHD risk. By aligning our categories with the biological basis of the conditions, we aim to enhance the precision of our analyses, grounding our findings in relevant physiological mechanisms. In negative control designs, we focused on maternal exposure conditions that had corresponding data collected from fathers, ensuring comparability between maternal and paternal information despite slight differences in the questionnaires. Due to the absence of queries regarding paternal thyroid conditions and restriction of paternal report to unspecified diabetes types, the negative control analysis for the endocrine category assessed overall diabetes for comparability between maternal and paternal exposure groups (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Using maternal data, we further investigated how exposure to different types of diabetes in pregnant mothers affected the risk of ADHD in offspring.\u003c/p\u003e\u003cp\u003eCovariates\u003c/p\u003e\u003cp\u003eTo ensure that covariate selection was rooted in existing knowledge of relevant causal pathways, we first selected potential covariates based on previous research investigating maternal immune-mediated conditions as ADHD risk factors\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan additionalcitationids=\"CR39 CR40 CR41\" citationid=\"CR39\" class=\"CitationRef\"\u003e38\u003c/span\u003e–\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, and available data. For each analysis we planned to conduct, covariates were evaluated for associations with both exposure and ADHD outcome to identify potential confounding. Directed acyclic graphs (DAGs) are effective tools for exploring complex causal relationships because they help clarify and visually represent pathways between variables\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. This can prevent over-adjustment or unnecessary inclusion of covariates that do not contribute additional control, thereby reducing the risk of introducing collider bias or overfitting models \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. We used Dagitty models\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e to define minimal sufficient adjustment sets of covariates for each specific analysis. Information on covariates selected is available in Table\u0026nbsp;1 (selection process details in Tables S2-4 and Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-10; handling of missing data described in Supplementary file).\u003c/p\u003e\u003cp\u003eStatistical Analysis\u003c/p\u003e\u003cp\u003eAnalyses were performed using SPSS version 27 and Stata version 17.\u003c/p\u003e\u003cp\u003eCrude and adjusted hazard ratios (HRs and aHRs) for ADHD with 95% confidence intervals (CIs) were estimated using Cox proportional hazard models. Separate analyses were conducted for each overall group and subgroups. The child’s age served as time variable, and follow-up started on the child’s third birthday, concluding with either an ADHD diagnosis, emigration, death, or by December 31st, 2017, whichever occurred first. Children were followed up until age 8–18 years. In our analysis, comparisons for one immune condition exposure (present/absent) included children who may have also been exposed to other immune conditions.\u003c/p\u003e\u003cp\u003eTo separate the effects of maternal immune-mediated responses during pregnancy from shared genetic factors, a negative control strategy was utilized. Previous studies have conducted negative control analyses by comparing outcomes of maternal exposures during pregnancy with paternal exposures or those of other relatives\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. This approach tested associations between paternal immune-mediated conditions—which are not expected to directly impact the fetal environment beyond genetic/epigenetic effects—and offspring ADHD risk. Both maternal and paternal analyses are subject to similar confounding factors; however, except for paternal epigenetic influences and potential genetic effects on the placental environment\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, maternal conditions predominantly affect the gestational milieu. Stronger associations with maternal immune-mediated conditions compared to paternal ones suggest an influence of maternal immune-mediated responses during pregnancy. Conversely, equal maternal and paternal associations imply that shared genetic and confounding factors are likely explanations. To prevent any bias that might occur if an observed association for one parent was driven by correlated conditions in the other parent, maternal and paternal associations were mutually adjusted for each other, as well as for the minimal sufficient adjustment sets of covariates.\u003c/p\u003e\u003cp\u003eTo address multiple testing – five tests within each family of tests (allergic conditions and other immune conditions) – we adjusted the alpha level to 0.01.\u003c/p\u003e\u003cp\u003eFinally, sensitivity analyses examined the potential impact of folate use during pregnancy, recognizing its role in immune system balance\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Sensitivity analyses assessing effects of medical treatments were also performed.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDescriptives\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;1 shows descriptive statistics for covariates. Amongst the children, 3 600 were diagnosed with ADHD (3.5%).\u003c/p\u003e\u003cp\u003e[Insert Table\u0026nbsp;1 here]\u003c/p\u003e\u003cp\u003eOverall Categories: Allergic and Other Immune Conditions\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;2 presents the risk estimates for the overall categories of maternal immune-mediated conditions. Both categories showed increased ADHD risk: allergic conditions (aHR = 1.23, CI: 1.14,1.34) and other immune conditions (aHR = 1.36, CI: 1.21,1.53). These findings suggest a broad impact of maternal immune health on offspring ADHD risk.\u003c/p\u003e\u003cp\u003e[Insert Table\u0026nbsp;2 here]\u003c/p\u003e\u003cp\u003eAsthma\u003c/p\u003e\u003cp\u003eAsthma emerged as a significant factor in increasing ADHD risk. As indicated in Table\u0026nbsp;2, maternal asthma was associated with a substantial risk increase (aHR = 1.47, CI: 1.30,1.67). The negative control analysis in Fig.\u0026nbsp;2 pointed to a similar pattern with paternal asthma (aHR = 1.26, CI: 1.10,1.45), underscoring the importance of asthma in both maternal and paternal histories.\u003c/p\u003e\u003cp\u003e[Insert Fig.\u0026nbsp;2 here]\u003c/p\u003e\u003cp\u003eAllergies\u003c/p\u003e\u003cp\u003eIn examining allergies, and as can be seen in Table\u0026nbsp;2, we found that any maternal allergy increased ADHD risk (aHR = 1.20, CI: 1.10,1.31). Interestingly, Fig.\u0026nbsp;2 reveals contrasting effects of maternal and paternal pollen allergies, with maternal pollen allergies linked to elevated risk (aHR = 1.26, CI: 1.12,1.41), whereas paternal pollen allergies suggested a preventive effect (aHR = 0.81, CI: 0.72,0.92). This difference between maternal and paternal exposure was statistically significant (X2 (df = 1, N = 64167) = 26.49, p \u0026lt; .001).\u003c/p\u003e\u003cp\u003eGastrointestinal conditions\u003c/p\u003e\u003cp\u003eMaternal gastrointestinal conditions overall (including the conditions Crohn’s disease (CD), ulcerative colitis (UC), and coeliac disease) did not reveal a significant association; however, the negative control analysis that specifically assessed Crohn’s disease and ulcerative colitis (CD/UC) revealed significant effects of maternal CD/UC (aHR = 1.95, CI: 1.23,3.09), but not of paternal CD/UC. Figure\u0026nbsp;2 shows that the hazard ratios for maternal versus paternal CD/UC were quite high; however, confidence intervals were wide, and the statistical difference only approached significance (X2 (df = 1, N = 70820) = 3.75, p = .053).\u003c/p\u003e\u003cp\u003eRheumatologic/Musculoskeletal Conditions\u003c/p\u003e\u003cp\u003eThe overall category of maternal rheumatologic/musculoskeletal conditions (including the conditions rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus, and fibromyalgia syndrome) were in the initial analysis associated with increased ADHD risk (aHR = 1.64, CI: 1.28,2.10). However, the exposure in the negative control analysis was limited to assess the conditions RA and AS and showed a similar trend for maternal exposure but not for paternal exposure.\u003c/p\u003e\u003cp\u003eEndocrine Conditions and Diabetes\u003c/p\u003e\u003cp\u003eMaternal endocrine conditions (including type 1 diabetes (T1D) and thyroid conditions) showed an increased risk of offspring ADHD (aHR = 1.42, CI:1.15,1.77). The negative control analysis, investigating any type of diabetes, displayed an effect of maternal diabetes (aHR = 1.39, 95% CI: 1.02,1.90) but not one of paternal diabetes. Analyzing type 1 diabetes (T1D), type 2 diabetes (T2D) and gestational diabetes (GD) separately (mothers only), offspring ADHD risk increased only with maternal T1D (aHR 2.50, 95% CI:1.66–3.75) (Table\u0026nbsp;3). No significant associations were noted for maternal type 2 diabetes (T2D) and gestational diabetes (GD).\u003c/p\u003e\u003cp\u003e[Insert Table\u0026nbsp;3 here]\u003c/p\u003e\u003cp\u003eSensitivity Analyses\u003c/p\u003e\u003cp\u003eSensitivity analyses (Table S9-10 in supplementary file) found no interactions between folic acid and specific conditions, or any effects of medical treatments on offspring ADHD risk.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings suggest that maternal immune-mediated conditions, both allergic and other immune conditions, are associated with a higher risk of ADHD in offspring. Specifically, maternal asthma is associated with a 47% higher risk, allergies with a 20% higher risk, rheumatologic/musculoskeletal conditions with a 64% higher risk, and endocrine conditions with a 42% higher risk. When examining a smaller sample with information on both paternal and maternal conditions available, asthma was the only paternal condition linked to an increased ADHD risk in offspring, showing a 26% higher risk. In comparison, for maternal conditions increased risk of ADHD in offspring was found with; asthma (33% higher risk), pollen allergies (26% higher risk), Crohn's disease/ulcerative colitis (CD/UC) (95% higher risk), and any type of diabetes (39% higher risk). Notably, the difference in risk between maternal and paternal conditions was only significant for pollen allergies, where maternal and paternal associations showed opposing directions. Comparison of maternal diabetes subtypes revealed that type 1 diabetes was associated with a 150% higher risk of ADHD in offspring, while type 2 diabetes and gestational diabetes were not significantly associated with ADHD risk. This underscores the role of type 1 diabetes in the observed association between any maternal diabetes and ADHD risk. Information on the diabetes type was not available for fathers, limiting our analysis of paternal diabetes.\u003c/p\u003e\u003cp\u003eThis study consistently found higher ADHD risk associated with maternal immune-mediated conditions compared to paternal ones, particularly allergies, which showed significant directional differences. While maternal conditions uniformly showed trends toward increased ADHD risk, paternal conditions exhibited more variability, with only asthma showing a significant association. Previous research has indicated higher ADHD risk after exposure to maternal, compared to paternal, autoimmune and atopic disorders, with similar findings regarding risk of autism spectrum disorder (autism)\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, suggesting potential maternal-specific immune mechanisms during pregnancy.\u003c/p\u003e\u003cp\u003eMaternal Immune Activation and Fetal Development\u003c/p\u003e\u003cp\u003eMaternal exposure to immune-mediated conditions during pregnancy could heighten offspring ADHD risk through mechanisms involving maternal immune activation, likely impacting fetal development via the placenta\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Research on \"fetal programming\" underscores the placenta's significance as the first functional organ of the fetus, facilitating maternal-fetal cellular interactions\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan additionalcitationids=\"CR51 CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e50\u003c/span\u003e–\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, which may influence fetal immune system development\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Disruptions in these interactions may potentially contribute to neuropsychiatric conditions like ADHD and autism\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e54\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Studies associating neurodevelopmental conditions and traits with prenatal exposure to maternal antibodies\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e suggest that maternal immune-mediated conditions may impact neurodevelopment through antibody-mediated pathways, including potential transference across the placenta and placental cytokine expression. Different maternal immune conditions can uniquely impact fetal development through a range of mechanisms, some of which overlap while others are distinct, as detailed in the following sections. These mechanisms encompass aspects, such as immune activation, response shifts, antibody transfer, metabolic influences, dopaminergic system interactions, and genetic and epigenetic factors.\u003c/p\u003e\u003cp\u003eMaternal Immune Response Shifts during Pregnancy\u003c/p\u003e\u003cp\u003eDuring normal pregnancies, the maternal immune response shifts from Th1 (cell-mediated) to Th2 (humoral) dominance\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, reducing inflammatory cytokine production, while increasing regulatory T-cell (Treg) production\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. This shift can have varying implications for maternal immune-mediated conditions. Atopic conditions, such as asthma and allergies, are typically Th2-dominant, and the enhanced Th2 response during pregnancy could exacerbate these conditions due to increased humoral activity\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Conversely, autoimmune conditions (such as RA, CD, UC) that are predominantly Th1-mediated may experience symptom improvement during pregnancy, as the Th2 shift downregulates typical inflammatory pathways\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. However, this shift in maternal immune response also results in elevated anti-inflammatory cytokine levels in maternal blood\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, which again may influence brain development pathways. Evidence from animal models suggests that maternal immune activation may reduce the accumulation of Tregs at the maternal-fetal interface, and that reversing this may reduce adverse neurodevelopmental outcomes\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. The mechanism by which maternal immune molecules influence fetal immune system and neurodevelopment, therefore, remains uncertain\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe placenta may play a pivotal role in modulating these effects. It contains its own macrophages, Hofbauer cells, producing various cytokines and chemokines\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. In response to maternal inflammation, the placenta may release cytokines and chemokines into fetal circulation, potentially affecting ongoing fetal growth and neurodevelopment\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e62\u003c/span\u003e,\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Cytokine release and subsequent inflammation are also key factors in altering dopaminergic systems, a feature strongly associated with ADHD.\u003c/p\u003e\u003cp\u003eMoreover placental inflammation can activate microglia\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, immune cells essential for neurodevelopmental processes, including axon guidance and synapses pruning\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e64\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. Activated excessively, microglia can release pro-inflammatory cytokines and proteins, potentially harming neurons and disrupting neurodevelopment\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNeurodevelopmental effects may also be mediated by activation of placental Toll-like receptors, which respond to various environmental threats\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSince Th2 dominance during pregnancy may result in exaggerated anti-inflammatory responses that intensify atopic conditions such as asthma and allergies\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, this heightened immune activity could amplify its influence on fetal development, potentially altering neurodevelopmental pathways and increasing ADHD risk. Autoimmune conditions characterized by Th1 dominance may experience symptom improvement during pregnancy due to reduced inflammation\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e, potentially diminishing the fetal risk associated with maternal exposure to these conditions.\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePlacental Antibody Transfer\u003c/p\u003e\u003cp\u003eInitially, only IgG antibodies were believed to cross the placenta, typically from the 13th week of gestation \u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. IgG autoantibodies play a significant role in autoimmune and inflammatory conditions, such as rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), fibromyalgia syndrome (FMS)\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e, and this study found associations between maternal rheumatologic musculoskeletal conditions, especially SLE and FMS, and ADHD risk. Maternal SLE has previously been linked to increased risk of neurodevelopmental disorders or other developmental challenges, particularly in boys\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, possibly due to placental transfer of maternal IgG autoantibodies\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e73\u003c/span\u003e,\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. Similarly, transferring IgG autoantibodies from FMS patients to mice has been shown to induce sensory hypersensitivity, suggesting a potential mechanism for maternal FMS impacting offspring neurodevelopment\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. While placental transfer of IgG antibodies is long recognized, recent evidence suggests that IgE autoantibodies can also be transferred across the placenta, though indirectly through immune complex linkage\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR28\" class=\"CitationRef\"\u003e27\u003c/span\u003e–\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Atopic conditions like asthma and allergies often involve elevated IgE levels\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Maternal asthma and allergies were associated with offspring ADHD risk, and effect estimates were higher than for paternal exposure. Elevated IgE and resulting inflammation may contribute to irregularities in fetal brain development. The trend of higher ADHD risk after prenatal exposure to maternal eczema only approached significance, which could be due to the lack of differentiation between intrinsic and extrinsic types of eczema, which are associated with different levels of IgE\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. On the other hand, another study that measured prenatal IgE did not find an association with offspring ADHD outcomes\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e, which underscores the need for further research.\u003c/p\u003e\u003cp\u003eDopaminergic System and Immune Interaction\u003c/p\u003e\u003cp\u003eImpairments in the dopaminergic system are recognized as a significant mechanism in ADHD\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e77\u003c/span\u003e,\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e, with studies linking genes like dopamine receptor D4 and the dopamine transporter to the disorder\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. Dopamine receptors on immune cells suggest dopamine involvement in immune-inflammatory responses\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. Dysregulation of peripheral dopamine levels is linked to rheumatoid arthritis and inflammatory bowel disease\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e80\u003c/span\u003e,\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. Alterations in dopamine pathways due to maternal immune conditions could contribute to the increased ADHD risk observed in offspring. Maternal immune activation in rats affects offspring dopaminergic signaling\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e, and, given dopamine’s role in ADHD\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e and immune disorders\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e62\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e, dopamine dysregulation presents a common mechanism and plausible link. Our study supports this, showing increased ADHD risk with maternal rheumatologic/musculoskeletal conditions and maternal CD/UC.\u003c/p\u003e\u003cp\u003eDiabetes and ADHD Risk - autoimmune inflammation vs metabolic influences\u003c/p\u003e\u003cp\u003eWe observed a strong association between maternal Type 1 Diabetes (T1D) and the risk of ADHD in offspring, consistent with previous research\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan additionalcitationids=\"CR41\" citationid=\"CR41\" class=\"CitationRef\"\u003e40\u003c/span\u003e–\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Despite few maternal T1D cases in the diabetes group (N = 301 of 1 425), analyzed separately, maternal T1D HR was notably high (HR = 2.5). In contrast, other diabetes types such as maternal Type 2 Diabetes (T2D) and Gestational Diabetes Mellitus (GDM) showed no individual associations with offspring ADHD risk.\u003c/p\u003e\u003cp\u003eUnfortunately, fathers did not specify diabetes type, limiting direct comparison of maternal and paternal T1D exposure. Instead, the broader exposure category “any diabetes” was compared between mothers and fathers. Any maternal diabetes exposure had higher HRs than any paternal diabetes, though not significantly different. This could be due to the inclusion of all diabetes types causing group heterogeneity.\u003c/p\u003e\u003cp\u003eGDM, emerging during pregnancy\u003csup\u003e\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e, shares features like insulin resistance with T2D and lacks T1D’s autoimmune aspect\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. While T1D involves autoantibodies against insulin-producing cells\u003csup\u003e31\u003c/sup\u003e, T2D’s immune role centers on low-grade inflammation and insulin resistance\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The significant increase in offspring ADHD risk with maternal T1D, and not with other diabetes types, may be explained by the autoimmune inflammation impacting fetal neural development, in contrast to the metabolic influences of other diabetes types.\u003c/p\u003e\u003cp\u003eGenetic and Epigenetic Influences\u003c/p\u003e\u003cp\u003eMaternal and paternal asthma were both linked to offspring ADHD, aligning with recent cohort studies in Denmark and Taiwan\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. A recent meta-analysis also reported a phenotypic association between ADHD and asthma, suggesting shared familial factors (genetic liability and/or shared environmental factors) contributing to their risk\u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eADHD and many immune-mediated conditions have heritable components\u003csup\u003e\u003cspan additionalcitationids=\"CR86\" citationid=\"CR86\" class=\"CitationRef\"\u003e85\u003c/span\u003e–\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e and their high comorbidity\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e suggest shared genetic variations. Genetic and epigenetic factors, influencing gene expression timing and location, and possibly influenced by prenatal environment\u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e, are implicated in autoimmune and atopic disorder development\u003csup\u003e\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e. These genetic and epigenetic changes could affect brain development processes, contributing to ADHD expression. Research suggests that epigenetic modifiers affecting DNA methylation (DNAm) and histone remodeling are crucial for normal neurodevelopment\u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e. DNAm is extensively studied as an epigenetic marker of ADHD\u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e, due to its role in brain maturation and function\u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e, susceptibility to genetic and environmental influences\u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e93\u003c/span\u003e,\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e, and links to various health issues, including immune-mediated conditions\u003csup\u003e\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u003c/sup\u003e and psychiatric disorders\u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eStrengths and limitations\u003c/p\u003e\u003cp\u003eThis study has several strengths. Data were drawn from an extensive birth cohort, facilitating detection of nuanced differences in ADHD risk across various groups and allowing for comparison between maternal gestational exposure and paternal exposure, offering insights into the complex interplay of environmental and genetic factors. Prospective data collection spanned multiple pregnancy exposures, with 8–18 years of follow-up. Additionally, the alpha level was adjusted to mitigate the risk of false positives.\u003c/p\u003e\u003cp\u003eThe study has limitations that could impact generalizability. Firstly, the 41% participation rate in MoBa could introduce selection bias, as participants are typically healthier and better educated than the overall population\u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e96\u003c/span\u003e,\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e. However, previous research found associations between various exposures and outcomes in MoBa participants and the total population to be comparable\u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e96\u003c/span\u003e,\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e. Children with ADHD in MoBa show similar functioning and psychosocial challenges as those in the broader Norwegian population\u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e. Simulations suggest that associations between risk factors and health outcomes remain robust even with underrepresented groups in the sample\u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e. Secondly, the oldest children in the sample may have received ADHD diagnoses before individual diagnoses were recorded in NPR, potentially resulting in false negatives if they only sought specialist healthcare in their early years(\u0026lt; 2008). Thirdly, self-reported medical conditions may be biased. Men with symptoms similar to women may receive more thorough treatment\u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e, potentially affecting diagnosis rates. Moreover, unclear distinctions between immune disease types and diagnosis delays\u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e can impact report accuracy. Reliable research depends on accurate data collection; misclassification of cases can dilute the effects. Fourthly, there is a significant amount of missing data for maternal ADHD symptoms, with approximately 49% missing. Although we used multiple imputation to address this issue, it is possible that the data missingness is not random, as ADHD symptoms could affect the likelihood of completing questionnaires. The results should therefore be interpreted with this consideration in mind. Fifthly, we acknowledge that some covariates might not have shown significant associations due to measurement imperfections or sample-specific characteristics, potentially leading to their exclusion despite theoretical relevance. Also, ~ 70% of fathers lacked information regarding ADHD symptoms. Consequently, we did not include paternal ADHD symptoms as a covariate, though this could be a potential confounder, particularly between paternal immune-mediated conditions and offspring ADHD. However, significant associations between maternal immune-mediated conditions and offspring ADHD persisted after adjusting for maternal ADHD symptoms. Conversely, associations with paternal conditions were weaker, even without adjusting for paternal ADHD symptoms. Sixthly, comparisons made for one immune condition exposure could include children exposed to additional immune conditions, which complicates the isolation of the specific impact of each condition. Seventhly, our data on asthma is not specific with regards to atopy. Eightly, in analyses comparing maternal gestational immune-mediated conditions with paternal immune-mediated conditions, paternal influence during gestation cannot be discounted, given animal studies indicating the paternal genome may impact placental development through genomic imprinting\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e. Lastly, maternal medical treatment during gestation, could affect associations. However, sensitivity analyses revealed no interactions between medical treatments and conditions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis large population-based cohort revealed increased offspring ADHD risk when mothers had certain immune-mediated conditions during pregnancy. Paternal asthma was also associated with offspring ADHD, implying some shared mechanisms involving genetic/epigenetic influences established at the time of conception. Maternal conditions may additionally have direct effects on fetal development through the maternal-fetal interface, potentially altering immune responses and increasing ADHD risk. The complex interplay of genetic/epigenetic, immune, environmental, and placental factors likely contributes to these associations. Further research is needed to explore the specific genetic and epigenetic pathways, as well as to identify precise immune and environmental factors that may mediate these risks. Longitudinal studies incorporating advanced biomarker analyses and detailed environmental exposure assessments could provide more comprehensive insights into the causal pathways and potential intervention points. Additionally, investigating whether these findings are consistent across diverse populations and settings would enhance the generalizability of our conclusions.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAttention\u0026ndash;deficit/hyperactivity disorder\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMoBa\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Norwegian Mother, Father, and Child Cohort Study\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMBRN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Medical Birth Registry of Norway\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNPR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Norwegian Patient Registry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIgE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmunoglobulin E\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIgG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eImmunoglobulin G\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCrohn\u0026rsquo;s disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUlcerative colitis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRheumatoid arthritis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnkylosing spondylitis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSLE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSystemic lupus erythematosus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFMS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFibromyalgia syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT1D\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eType 1 diabetes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate \u003c/h2\u003e\n\u003cp\u003eThe study was approved by The Regional Committee for Medical and Health Research Ethics (2014/2266).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConsent for publication \u003c/h2\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eData from the Norwegian Mother, Father and Child Cohort Study and the Medical Birth Registry of Norway used in this study are managed by the national health register holders in Norway (Norwegian Institute of public health) and can be made available to researchers, provided approval from the Regional Committees for Medical and Health Research Ethics (REC), compliance with the EU General Data Protection Regulation (GDPR) and approval from the data owners. The consent given by the participants does not open for storage of data on an individual level in repositories or journals. Researchers who want access to data sets for replication should apply through helsedata.no. Access to data sets requires approval from The Regional Committee for Medical and Health Research Ethics in Norway and an agreement with MoBa.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eFunding is provided by the National Institute of Child Health and Human Development (NICHD), Grant/Award Number: R01HD090051, and by The Research Council of Norway, Grant/Award Number: 248983.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eAll authors (KMW, RBA, KG, SM, PM, ES, WIL, CS, MB, TRK, MH, HA) contributed to the planning of the project, including research questions, design, use of methods, etc. KMW cleaned and analyzed the data. KG provided statistical advice. KMW prepared all tables and figures. All authors interpreted results. KMW drafted the manuscript. All authors contributed to revise the manuscript, and all approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this on-going cohort study. A special thanks also to Christine Roth for contributing with information and scripts regarding folate use during pregnancy in the MoBa sample for our sensitivity analysis.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFaraone SV, Bellgrove MA, Brikell I, et al. 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Paternally expressed genes predominate in the placenta. \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e. 2013;110(26):10705-10710. doi:doi:10.1073/pnas.1308998110\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTABLE 1 Descriptive Statistics for Covariates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003eTotal Sample,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 104270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eBirth year, \u003cem\u003en\u003c/em\u003e, mean, [SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e104 270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e2005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e[2,217]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eMothers\u0026rsquo; age, \u003cem\u003en,\u003c/em\u003e mean, [SD]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e104 270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e30,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e[4,666]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eMothers\u0026rsquo; ADHD symptoms\u0026apos; score, \u003cem\u003en\u003c/em\u003e, mean, [SD] \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e52 947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e2,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e[0,576]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eMissing data on mothers\u0026rsquo; ADHD symptoms\u0026rsquo; scores, \u003cem\u003en,\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e51 322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(49,22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eHighest level of education among parents, \u003cem\u003en,\u0026nbsp;\u003c/em\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Less than high school graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e3 495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(3,35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;High school graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e23 250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(22,30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Undergraduate education completed\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e34 055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(32,66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Postgraduate education (masters or doctorate) completed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e28 754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(27,58)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Missing data on level of education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e14 715\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(14,11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eParents\u0026rsquo; relationship status, \u003cem\u003en,\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Married or in a relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e90 754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(87,04)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Single\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e3 181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(3,05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Missing data on parents\u0026rsquo; relationship status\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e10 334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(9,91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eParity, \u003cem\u003en,\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;First born\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e45 545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(43,68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Second born\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e37 678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(36,14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Third (or more) born\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e21 046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(20,18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eMother\u0026apos;s smoking habits, \u003cem\u003en,\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mothers smoking before pregnancy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e26 326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(25,25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mothers not smoking before pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e66 269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(63,56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Missing data on smoking habits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e11 674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(11,20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eAlcohol use before pregnancy,\u003cem\u003e\u0026nbsp;n,\u003c/em\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e6 555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(6,29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Less than 3 units per month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e57 620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(55,26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;1-3 units per week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e22 489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(21,57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;4-7 units per week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(0,91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Missing data on alcohol use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e16 657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(15,98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003eThe mother\u0026rsquo;s previous mental disorders, \u003cem\u003en,\u0026nbsp;\u003c/em\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Previously diagnosed with anorexia, bulimia, or other eating \u0026nbsp;aadisorders, depression or anxiety\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e19 264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(18,48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 399px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Never diagnosed with anorexia, bulimia, or other.eating \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; a \u0026nbsp;disorders, depression or anxiety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 83px;\"\u003e\n \u003cp\u003e85 005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e(81,52)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTABLE 2 Associations Between Maternal Immune-Mediated Conditions During Pregnancy and ADHD in Offspring Examined with Cox Proportional Hazard Analyses\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 23px;\"\u003e\n \u003cp\u003eCrude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 25px;\"\u003e\n \u003cp\u003eAdjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eNo, of Person-Months at observed risk\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eIncidence Rate\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eHazard Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eHazard Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eAsthma/Allergic/Atopic Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e10016598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e22,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e3106811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e27,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,11-1,30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,14-1,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eAutoimmune/ Inflammatory Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e13948303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1078983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e29,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,17-1,47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,21-1,53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 30px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eAsthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e13939521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e22,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e743603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e36,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,42-1,83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,30-1,67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eAny Allergy (pollen, animal, other)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e11181584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2385555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e26,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,04-1,24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,10-1,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eAtopic Eczema\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14248317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e548285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e24,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0,89-1,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0,95-1,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eUrticaria/Hives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14625830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e110415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e26,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0,77-1,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0,77-1,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,574\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003ePsoriasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14815126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e239105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e28,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0,93-1,51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0,89-1,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,296\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eGastrointestinal Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e15052760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e108500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e27,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0,83-1,73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0,89-1,85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eRheumatologic/Musculoskeletal Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14966233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e154198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e42,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,41-2,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,28-2,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 30px;\"\u003e\n \u003cp\u003eEndocrine Conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14609045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 8px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e298589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e30,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1,32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,07-1,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e0,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,15-1,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0,001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003e\n \u003cp\u003eNote: Separate analyses were performed for each of the exposure variables. CI, Confidence interval; Ref, reference group to which mothers with immune-mediated disorders are compared. The \u0026alpha; level was set to .01 to indicate significant associations. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Each analyses used specific adjustment sets of covariates: Asthma/Allergic/Atopic Conditions: child\u0026apos;s birth year, mother\u0026apos;s parity, alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Autoimmune/Inflammatory Conditions: child\u0026apos;s birth year, parental relationship status, mother\u0026apos;s age, parity, smoking and alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Asthma: parental relationship status, mother\u0026apos;s age, parity, smoking and alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Any Allergy: child\u0026apos;s birth year, parental educational attainment, mother\u0026apos;s age, parity, smoking and alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Atopic Eczema: child\u0026apos;s birth year, parental educational attainment, mother\u0026apos;s parity, alcohol use before pregnancy, previous mental disorders and self‐reported ADHD symptoms; Urticaria/Hives: parental educational attainment, mother\u0026apos;s parity and alcohol use before pregnancy; Psoriasis: parental educational attainment and relationship status, mother\u0026apos;s smoking and previous mental disorders; Gastrointestinal Conditions: child\u0026apos;s birth year, mother\u0026apos;s age and previous mental disorders; Rheumatologic/Musculoskeletal Conditions: parental educational attainment and relationship status, mother\u0026apos;s parity, smoking and alcohol use before pregnancy, and self‐reported ADHD symptoms; Endocrine Conditions (T1D and hyper/hypothyroidism): child\u0026apos;s birth year, parental educational attainment, mother\u0026apos;s age, parity, smoking and alcohol use before pregnancy, and self‐reported ADHD symptoms.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Observation period between January 2008 and December 2017 for participants born in or before January 2008.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Per 100 000 person-months under observed risk.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"945\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 945px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTABLE 3 Associations Between Different Types of Maternal Diabetes in Pregnancy and ADHD in Offspring Examined with Cox Proportional Hazard Analyses\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 58px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 257px;\"\u003e\n \u003cp\u003eCrude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 292px;\"\u003e\n \u003cp\u003eAdjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003eNo, of Person-Months at observed risk\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eIncidence Rate\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eHazard Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eHazard Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 132px;\"\u003e\n \u003cp\u003eDiabetes 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e14972880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e23,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e43263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e57,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e2,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0,51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1,66-3,73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e2,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1,66-3,75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026lt;,001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 132px;\"\u003e\n \u003cp\u003eDiabetes 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e14972880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e23,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e21993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e22,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0,64-1,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0,944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0,64-1,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e0,940\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 132px;\"\u003e\n \u003cp\u003eGestational diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e14972880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e23,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 86px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 36px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 112px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003e140489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e27,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0,97-1,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0,259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e1,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003e0,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0, 96-1,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e0,341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"top\" style=\"width: 945px;\"\u003e\n \u003cp\u003eNote: Separate analyses were performed for each type of diabetes. CI, Confidence interval; Ref, reference group to which mothers with diabetes are compared. The \u0026alpha; level was set to .01 to indicate significant associations. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"top\" style=\"width: 945px;\"\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Analyses are adjusted for the following covariates: \u0026nbsp;child\u0026apos;s birth year, parental educational attainment, mother\u0026apos;s age, parity, smoking and alcohol use before pregnancy, and self‐reported ADHD symptoms.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"top\" style=\"width: 945px;\"\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Observation period between January 2008 and December 2017 for participants born in or before January 2008.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" valign=\"top\" style=\"width: 945px;\"\u003e\n \u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Per 100 000 person-months under observed risk.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ADHD, immune-mediated conditions, pregnancy, MoBa, MBRN","lastPublishedDoi":"10.21203/rs.3.rs-5594521/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5594521/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBACKGROUND\u003c/h2\u003e \u003cp\u003eMaternal immune-mediated conditions during pregnancy have been linked with increased risk of attention-deficit/hyperactivity disorder (ADHD) in offspring. However, we do not know the extent to which these associations are influenced by shared genetic predispositions, as opposed to maternal inflammatory/immune responses during pregnancy. This study contributes by using paternal immune-mediated conditions as a negative control to explore these underlying factors, as we investigate associations between maternal immune-mediated conditions during pregnancy and offspring ADHD.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eProspective data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) was linked with the Medical Birth Registry of Norway (MBRN) and the Norwegian Patient Registry (NPR) to assess associations between prenatal exposure to maternal immune-mediated conditions and offspring ADHD risk up to age 18. Nationwide recruitment from 1999 to 2008 resulted in 104,270 eligible mother-child pairs. Among these, 21,340 children were exposed to maternal allergic conditions (asthma, allergies, atopic conditions) and 7,478 to other immune conditions (autoimmune, inflammatory). Paternal self-reported immune conditions served as negative controls for genetic confounding. Data was mostly collected through MoBa, with additional maternal condition cases sourced from MBRN, and children\u0026rsquo;s ADHD diagnoses obtained from NPR. Cox proportional hazard models estimated Hazard ratios for ADHD diagnoses.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eBoth overall categories were associated with increased offspring ADHD risk (allergic conditions HR 1.23 95% CI, 1.14\u0026ndash;1.34; other immune conditions HR 1.36 95% CI, 1.21\u0026ndash;1.53). Specifically, we found associations for maternal asthma (HR 1.47 95% CI, 1.30\u0026ndash;1.67); allergies (HR 1.20 95% CI, 1.10\u0026ndash;1.31); rheumatologic/musculoskeletal conditions (HR 1.64 95% CI, 1.28\u0026ndash;2.10), Crohn\u0026rsquo;s disease/ulcerative colitis (adjusted HR 1.95 95% CI, 1.23\u0026ndash;3.09), and endocrine conditions (HR 1.42 95% CI, 1.15\u0026ndash;1.77), specifically, type 1 diabetes (adjusted HR 2.50 95% CI, 1.66\u0026ndash;3.75). Although some paternal immune-mediated conditions (psoriasis, ulcerative colitis, Crohn\u0026rsquo;s disease) showed similar trends of increased ADHD risk in offspring, only paternal asthma was significantly associated (adjusted HR 1.26 95% CI, 1.10\u0026ndash;1.45).\u003c/p\u003e\u003ch2\u003eCONCLUSIONS\u003c/h2\u003e \u003cp\u003eSeveral maternal immune-mediated conditions were associated with increased ADHD risk in offspring. Observations of higher, more consistent estimates of ADHD risk in offspring for most maternal immune-mediated conditions versus paternal ones indicate that unmeasured genetic confounding does not fully explain these associations. These results suggest direct effects on fetal development through events at the maternal-fetal interface which may alter fetal immune responses and potentially lead to greater risk of ADHD in the offspring. Asthma may be a possible exception to this mechanism, as paternal asthma was also linked with risk of offspring ADHD.\u003c/p\u003e","manuscriptTitle":"Maternal Immune-Mediated Conditions and ADHD Risk in Offspring","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-14 23:02:52","doi":"10.21203/rs.3.rs-5594521/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-02T10:24:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-29T15:28:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-17T13:34:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"56556521156364841157015795347375238764","date":"2025-04-15T13:20:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"91820370287845141082423846971933004062","date":"2025-04-12T09:34:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-10T01:45:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-03T08:13:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-03T08:11:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medicine","date":"2025-03-31T18:50:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bb140fb3-e1cd-4e9f-9b50-435888cee7c6","owner":[],"postedDate":"April 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-07T16:07:53+00:00","versionOfRecord":{"articleIdentity":"rs-5594521","link":"https://doi.org/10.1186/s12916-025-04227-3","journal":{"identity":"bmc-medicine","isVorOnly":false,"title":"BMC Medicine"},"publishedOn":"2025-07-01 15:58:34","publishedOnDateReadable":"July 1st, 2025"},"versionCreatedAt":"2025-04-14 23:02:52","video":"","vorDoi":"10.1186/s12916-025-04227-3","vorDoiUrl":"https://doi.org/10.1186/s12916-025-04227-3","workflowStages":[]},"version":"v1","identity":"rs-5594521","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5594521","identity":"rs-5594521","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}